code: def test_get_parameters2(self):
      pseudo_counts = {
          "A": [[1], [2], [3]],
          "B": [[4], [5]],
          "C": [[6, 6, 6, 6, 6, 6], [7, 7, 7, 7, 7, 7]],
      }
      cpds = set(
          [
              self.est3.estimate_cpd(
                  "A",
                  prior_type="dirichlet",
                  pseudo_counts=pseudo_counts["A"],
              ),
              self.est3.estimate_cpd(
                  "B",
                  prior_type="dirichlet",
                  pseudo_counts=pseudo_counts["B"],
              ),
              self.est3.estimate_cpd(
                  "C",
                  prior_type="dirichlet",
                  pseudo_counts=pseudo_counts["C"],
              ),
          ]
      )
      all_cpds = self.est3.get_parameters(
          prior_type="dirichlet", pseudo_counts=pseudo_counts, n_jobs=1
      )
      self.assertListEqual(
          sorted(cpds, key=lambda t: t.variables[0]),
          sorted(all_cpds, key=lambda t: t.variables[0]),
      )
  
imports: import unittest
  import numpy
  import pandas
  from joblib.externals.loky import get_reusable_executor
  from pgmpy import config
  from pgmpy.estimators import BayesianEstimator
  from pgmpy.factors.discrete import TabularCPD
  from pgmpy.models import BayesianNetwork
label_desc: Use image node_id 7 for calling the TestBayesianEstimatorTorch obj's underlying member method code with example usage: obj.test_get_parameters2() without return types